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OpenAI Agents SDK

OpenAI Agents SDK is a development toolkit for building autonomous agents, simplifying the orchestration of multi-agent workflows.

#Artificial Intelligence
#automation
#productive forces
#multimodal
#agent
OpenAI Agents SDK

Product Details

OpenAI Agents SDK is a development toolkit for building autonomous agents. It builds on OpenAI's advanced model capabilities, such as advanced reasoning, multi-modal interaction, and new security technologies, to provide developers with a simplified way to build, deploy, and scale reliable agent applications. The toolkit not only supports the orchestration of single-agent and multi-agent workflows, but also integrates observability tools to help developers track and optimize the execution process of agents. Its main advantages include easy-to-configure LLM models, intelligent agent handover mechanisms, configurable safety checks, and powerful debugging and performance optimization capabilities. This toolkit is suitable for businesses and developers who need to automate complex tasks and is designed to improve productivity and efficiency through agent technology.

Main Features

1
Supports the orchestration of single-agent and multi-agent workflows, simplifying the automation of complex tasks.
2
Provides an easy-to-configure LLM model with clear instructions and built-in tools.
3
The intelligent handover mechanism can intelligently transfer control rights between different agents according to task requirements.
4
Configurable security checks ensure input and output verification and ensure the safe operation of the agent.
5
Integrate observability tools to visualize agent execution trajectories for easy debugging and performance optimization.

How to Use

1
Visit the official OpenAI documentation for details and usage guidelines on the Agents SDK.
2
Install the Agents SDK and integrate it into your Python code base.
3
Define the agent, including name, instructions, and tools. For example, create a support agent that handles refund requests.
4
Configure the handover mechanism of the agent to route user requests to the correct agent based on task requirements.
5
Run the agent workflow and observe how the agent handles and responds by inputting user questions.
6
Use observability tools to debug and optimize the execution process of agents.
7
Extend the agent functionality as needed, adding new tools and logic.

Target Users

This product is suitable for enterprises and developers who need to build automated tasks and improve productivity, especially those that need to handle complex multi-step tasks, such as customer support automation, multi-step research, content generation, code review and sales prospect analysis, etc. Through agent technology, users can hand over tedious tasks to agents to complete, thereby focusing on more valuable work.

Examples

Coinbase uses Agents SDK to quickly prototype and deploy AgentKit, which enables AI agents to interact seamlessly with crypto wallets and on-chain activity.

Box leverages the Agents SDK and web search capabilities to create agents for enterprises, enabling them to securely search and extract insights from internal and public internet data.

Navan uses document search tools in its AI-powered travel agents to provide users with precise answers to knowledge base articles.

Quick Access

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Categories

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› AI model
› Development and Tools

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